The Internet of Orthopaedic Things (IoOT): A Multi-Framework Strategic Analysis of Smart Implants, Market Dynamics, and Future Research Frontiers

Abstract

Purpose: This paper explores the emerging ecosystem of the Internet of Orthopaedic Things (IoOT) and the integration of smart implants in modern musculoskeletal care. Using an exploratory and qualitative approach, the study aims to decode the strategic landscape of connected orthopaedic devices.

Design/Methodology: The research employs a multi-framework analytical approach, integrating SWOC, ABCD, and PESTLE analyses, alongside Impact Analysis, to evaluate the current and future status of smart implants. The information is collected using websites, search engines (like Google & Google Scholar) and AI-driven GPTs.

Findings: Preliminary analysis suggests that while smart implants significantly enhance real-time patient monitoring and postoperative outcomes, widespread adoption is hindered by high initial costs, data privacy concerns (GDPR/HIPAA), and a lack of standardized interoperability protocols.

Research Limitations/Implications: The study identifies a critical research gap in long-term bio-battery sustainability and the legal liability of AI-driven surgical recommendations.

Originality/Value: This paper provides a unique "Practitioner-Researcher Roadmap," offering actionable recommendations for stakeholders to navigate the IoOT transition by 2030.

Type of Paper: Review-based Qualitative Exploratory research analysis.